Quantitative Traits
Preliminaries
If you are already familiar with the structure of these exercises, read the Introduction first.
Note
Reminder: Save your work regularly.
Important
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Contact information
If you have questions about these exercises, please contact Dr. Kevin Middleton (middletonk@missouri.edu) or drop by Tucker 224.
Learning Objectives
The learning objectives for this exercise are:
- Explain how polygenic traits differ from Mendelian traits
- Explain how traits with continuous (also called quantitative) phenotypic measures result from the combined effects of many different genes
- Describe how many genes can each contribute a small amount to a phenotype
- Explain what quantitative trait loci (QTL) are and how QTL are discovered
- Explain how the contributions of many genes of small effect can be associated with a disease or condition
Contrasting Mendelian traits and polygenic traits
Dominant/recessive to just thinking about alternate alleles (major vs. minor)
What are quantitative traits?
Counting the ways: Binomial Coefficent
Continuous traits from combinations of many Mendelian traits
Figure 1 shows…FIXME
Combinations of alleles are binomial
Large numbers of small additions and subtractions are normal
Make some assumptions:
- Additivity can mean adding negative numbers
- All genes have roughly equal effect
- Gene do not interact with one another
Case study: Human height
The National Health and Nutrition Examination Survey (“NHANES”) began in the early 1960’s and continues to this day. The goal is to assess the health and nutrition status of a broad cross-section of the population. As part of this study, routine measurements of body size such as height (in cm) are recorded for each participant.
The 2017-2020 NHANES survey has data for 13,137 individuals.
Figure 2 shows…
Generating a normal distribution from combinations of alleles
Describing distributions
Using distributions
Associating QTLs with genetic variants
Intro SNP
Shapiro pigeon example (dominant trait)
QTL for Human Height
- Best understood quantitative trait in humans
- Yet still 700 genes
Yengo et al. (2018):
- ~700,000 individuals
- 3290 (“near-independent”) SNPs explain ~25% of the variation in human height among Europeans
- Estimated to be ~700 explaining ~16% of variation in 2010 (Lango Allen et al. 2010)
Case Study: Threshold traits
Schizophrenia (~200 genes)
Why family history is one of the most important diagnostic tools in medicine
References
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